Araştırma Makalesi

Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul

Cilt: 26 Sayı: 3 31 Temmuz 2026
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Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul

Öz

This research paper explores duration dynamics within the Borsa İstanbul (BIST) stock exchange by utilizing the Autoregressive Conditional Duration (ACD) model applied to the time between consecutive trades. The investigation of an appropriate error term specification demonstrates that the Weibull ACD (WACD) model is the most suitable choice of distribution. The application of the WACD model on the ten most actively traded stocks in the market reveals cross-sectional variations in the trade duration dynamics, where the degree of duration clustering varies even among the most liquid stocks in the market. The study indicates that the duration dynamics within the Borsa İstanbul are closer to those observed in developing markets, in terms of market microstructure and intraday liquidity, rather than those in developed markets. These findings provide insights for market participants and academics to better understand the trade duration dynamics within the BIST market.

Anahtar Kelimeler

Kaynakça

  1. Aldrich, E. M., Heckenbach, I., & Laughlin, G. (2014).The random walk of high frequency trading. arXiv preprint arXiv:1408.3650.
  2. Andersen, T., & Bollerslev, T. (1997). Intraday periodicity and volatility persistence in financial markets. Journal of Empirical Finance, 4(2–3), 115–158. https://doi. org/10.1016/S0927-5398(97)00004-2
  3. Andersen, T. G., & Bollerslev, T. (1998). Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts. International Economic Review, 39(4), 885. https://doi.org/10.2307/2527343
  4. Aquilina, M., Budish, E., & O’Neill, P. (2022). Quantifying the high-frequency trading “arms race.” The Quarterly Journal of Economics, 137(1), 493–564. https://doi. org/10.1093/qje/qjab032
  5. Balakrishna, N. & Rahul, T. (2014). Inverse Gaussian distribution for modeling conditional durations in finance. Communications in Statistics-Simulation and Computation 43(3): 476–486. https://doi.org/10. 1080/03610918.2012.705938
  6. Bauwens, L., & Giot, P. (2000). The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks. Annales d’Economie et de Statistique, 60, 117-149. https://doi.org/10.2307/20076257
  7. Bauwens, L. & Veredas, D. (2004). The Stochastic Conditional Duration Model: A Latent Factor Model for the Analysis of Financial Durations. Journal of Econometrics, 119, 381-412. https://doi.org/10.1016/ S0304-4076(03)00201-X
  8. Beltratti, A., & Morana, C. (1999). Computing value at risk with high frequency data. Journal of Empirical Finance, 6(5), 431–455. https://doi.org/10.1016/ S0927-5398(99)00008-0

Ayrıntılar

Birincil Dil

İngilizce

Konular

Ekonomi, İşletme

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

31 Temmuz 2026

Gönderilme Tarihi

21 Şubat 2023

Kabul Tarihi

28 Ocak 2026

Yayımlandığı Sayı

Yıl 2026 Cilt: 26 Sayı: 3

Kaynak Göster

APA
Karahan, C. C., & Baran, Ü. A. (2026). Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul. Ege Academic Review, 26(3), 365-384. https://doi.org/10.21121/eab.20260024
AMA
1.Karahan CC, Baran ÜA. Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul. eab. 2026;26(3):365-384. doi:10.21121/eab.20260024
Chicago
Karahan, Cenk C., ve Ümit Altay Baran. 2026. “Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul”. Ege Academic Review 26 (3): 365-84. https://doi.org/10.21121/eab.20260024.
EndNote
Karahan CC, Baran ÜA (01 Temmuz 2026) Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul. Ege Academic Review 26 3 365–384.
IEEE
[1]C. C. Karahan ve Ü. A. Baran, “Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul”, eab, c. 26, sy 3, ss. 365–384, Tem. 2026, doi: 10.21121/eab.20260024.
ISNAD
Karahan, Cenk C. - Baran, Ümit Altay. “Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul”. Ege Academic Review 26/3 (01 Temmuz 2026): 365-384. https://doi.org/10.21121/eab.20260024.
JAMA
1.Karahan CC, Baran ÜA. Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul. eab. 2026;26:365–384.
MLA
Karahan, Cenk C., ve Ümit Altay Baran. “Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul”. Ege Academic Review, c. 26, sy 3, Temmuz 2026, ss. 365-84, doi:10.21121/eab.20260024.
Vancouver
1.Cenk C. Karahan, Ümit Altay Baran. Investigation of the Trade Durations with Autoregressive Conditional Duration Model: Evidence from Borsa İstanbul. eab. 01 Temmuz 2026;26(3):365-84. doi:10.21121/eab.20260024